package com.example.wordcount;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

/**
 * Created with IntelliJ IDEA.
 * ClassName: WordCountStream
 * Package: com.example.wordcount
 * Description:
 * User: fzykd
 *
 * @Author: LQH
 * Date: 2023-07-17
 * Time: 10:52
 */

//流处理 读文件
//流处理 wordCount案例
public class WordCountStream {
    public static void main(String[] args) throws Exception {
        //1.创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        //2.读取数据
        DataStreamSource<String> lineDS = env.readTextFile("input/word.txt");

        //3.处理数据 切分 转换 分组 聚合
        //函数泛型 一个是输入类型 一个输出类型
        SingleOutputStreamOperator<Tuple2<String, Integer>> wordCountOne = lineDS.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public void flatMap(String s, Collector<Tuple2<String, Integer>> collector) throws Exception {
                //单词切分
                String[] s1 = s.split(" ");
                //循环的转换为二元组
                for (String word : s1) {
                    Tuple2<String, Integer> wordOne = Tuple2.of(word, 1);
                    //通过采集器 向下游发送数据
                    collector.collect(wordOne);
                }
            }
        });
        
        //分组
        KeyedStream<Tuple2<String, Integer>, String> tuple2StringKeyedStream = wordCountOne.keyBy(
                new KeySelector<Tuple2<String, Integer>, String>() {
                    @Override
                    public String getKey(Tuple2<String, Integer> stringIntegerTuple2) throws Exception {
                        return stringIntegerTuple2.f0;
                    }
                }
        );

        //组合
        SingleOutputStreamOperator<Tuple2<String, Integer>> sum = tuple2StringKeyedStream.sum(1);

        //4.输出数据
        sum.print();
        //5.执行
        env.execute();
    }
}
